Strategies for Cardiovascular Risk Assessment and Prevention Over the Life Course
Author(s) -
Ramachandran S. Vasan,
William B. Kannel
Publication year - 2009
Publication title -
circulation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.795
H-Index - 607
eISSN - 1524-4539
pISSN - 0009-7322
DOI - 10.1161/circulationaha.109.881995
Subject(s) - medicine , life course approach , risk assessment , course (navigation) , intensive care medicine , psychology , social psychology , computer security , computer science , physics , astronomy
Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality worldwide, including in the United States. Fortunately, the major risk factors contributing to the development of atherosclerotic CVD have been detailed in epidemiological studies, and randomized clinical trials have demonstrated the benefits of lowering elevated levels of risk factors. Yet, one of the most challenging questions in clinical medicine remains: if and when to treat and how best to treat individuals with ≥1 CVD risk factors.Article see p 384 A few concepts have helped us in identifying strategies to answer the question posed above. First, CVD risk develops over the entire life course as a result of the combined influences of lifestyle-related factors, environmental triggers, and genetic susceptibility. Second, clinically overt CVD usually is antedated by the presence of ≥1 risk factors and subclinical atherosclerosis. Such a time course of evolution provides us with a window of opportunity for prevention/intervention. The long latency of CVD means that preventive approaches also may vary over the life course. Third, CVD prevention is best thought of as a combination of “population-based” prevention, primary prevention in high-risk individuals, and secondary prevention in those with established clinical CVD.1 The exact proportion allocated to each of these 3 approaches varies, depending on the mean absolute CVD risk (and its distribution) in a given community and the healthcare resources available at hand. Fourth, with regard to the “high-risk individuals” approach, rates of CVD vary among people with identical levels of any particular risk factor based on the levels of other risk factors, emphasizing the multifactorial origin of CVD. Therefore, combining information about levels of different CVD risk factors in an individual using 1 or more risk prediction algorithms is the best approach for assessing the likelihood that he or she will experience a CVD …
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